5 citations · 7 across the 4 of their papers we have counts for
7 papers
Using CNNs to Identify the Origin of Finger Vein Image
Babak Maser, Andreas Uhl
We study the finger vein (FV) sensor model identification task using a deep learning approach. So far, for this biometric modality, only correlation-based PRNU and texture descript…
Identifying the Origin of Finger Vein Samples Using Texture Descriptors
Babak Maser, Andreas Uhl
Identifying the origin of a sample image in biometric systems can be beneficial for data authentication in case of attacks against the system and for initiating sensor-specific pro…
Two-stage CNN-based wood log recognition
Georg Wimmer, Rudolf Schraml, Heinz Hofbauer +2
The proof of origin of logs is becoming increasingly important. In the context of Industry 4.0 and to combat illegal logging there is an increasing motivation to track each individ…
Enabling Fingerprint Presentation Attacks: Fake Fingerprint Fabrication Techniques and Recognition Performance
Christof Kauba, Luca Debiasi, Andreas Uhl
Fake fingerprint representation pose a severe threat for fingerprint based authentication systems. Despite advances in presentation attack detection technologies, which are often i…
Improving Endoscopic Decision Support Systems by Translating Between Imaging Modalities
Georg Wimmer, Michael Gadermayr, Andreas Vécsei +1
Novel imaging technologies raise many questions concerning the adaptation of computer-aided decision support systems. Classification models either need to be adapted or even newly…
Demographic Bias: A Challenge for Fingervein Recognition Systems?
P. Drozdowski, B. Prommegger, G. Wimmer +4
Recently, concerns regarding potential biases in the underlying algorithms of many automated systems (including biometrics) have been raised. In this context, a biased algorithm pr…